Paper
16 August 2023 Research on parametric modeling of low-voltage switchgear based on OpenCascade
Zheng Cao, Wenhui Wang, Jiawei Li
Author Affiliations +
Proceedings Volume 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023); 127870G (2023) https://doi.org/10.1117/12.3004570
Event: 6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023), 2023, Shenyang, China
Abstract
In recent years, with the construction of electric energy and its related supporting infrastructure, the product iteration and update speed of the low-voltage complete switchgear industry has been gradually accelerated. Against the background of growing market demand year by year, adjusting product models according to customer requirements has gradually become the main production mode of low-voltage switchgear. In order to better improve the traditional production process, domestic and foreign research mainly revolves around the secondary development of various types of 3D CAD software. Although this can achieve a certain degree of design preview, it still lacks an effective interaction mechanism and intuitive modeling effect for the whole business flow. This paper is based on the framework of OpenCascade to parametrically model the low-voltage switchgear cabinet and key components. Combined with Qt as the front-end interaction, it provides a new solution for the customized production of low-voltage switchgear.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zheng Cao, Wenhui Wang, and Jiawei Li "Research on parametric modeling of low-voltage switchgear based on OpenCascade", Proc. SPIE 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023), 127870G (16 August 2023); https://doi.org/10.1117/12.3004570
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KEYWORDS
Modeling

Switching

Design and modelling

3D modeling

Circuit switching

Data modeling

Algorithm development

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